1. Field of the Invention
The present invention relates to a corneal topography analysis system and a method of performing corneal topography analysis.
2. Description of the Related Art
Corneal topography analysis systems are known which analyze the three-dimensional topography of the cornea to be examined by projecting a number of Placido rings onto the cornea, taking the Placido ring image created by the convex surface of the cornea by means of an image sensor, and finding data for the curvature of the cornea based on the taken Placido ring image. The corneal topography is displayed in terms of various kinds of color maps. The information about the corneal topography obtained by such an analysis system is utilized for planning an operation for correcting the cornea, for planning cataract surgery, and for postoperative evaluations. In addition, the topography is used for early discovery and diagnosis of keratoconus that is one of several corneal diseases.
As a diagnosis of keratoconus, a method of judging keratoconus topography using a neural network approach is disclosed by Michael K. Smolek et al. in “Current Keratoconus Detection Methods Compared With a Neural Network Approach, Investigative Ophthalmology & Visual Science, October 1997, Vol. 38, No. 11, pp. 2290-2299” (Reference 1), which is incorporated herein by reference. In this method, the presence of keratoconus (KC) and keratoconus suspects (KCS) are judged using a neural network and 10 indexes characterizing the corneal topography, i.e., Differential Sector Index (DSI), Opposite Sector Index (OSI), Center-Surround Index (CSI), Analyzed Area (AA), Cylinder (CYL), Irregular Astigmatism Index (IAI), the steep axis of simulated keratometry (SK1), Surface Regularity Index (SRI), Surface Asymmetry Index (SAI) and the Standard Deviation of corneal Power (SDP). Conventionally, however, only keratoconus topographies have been judged. The categories of corneal topographies and the display of the results of the analysis leave room for further improvement.
The spacing and number of Placido rings are different among manufacturers of corneal topography systems for calculating the indexes that are necessary for classification of keratoconus topographies. Furthermore, the number of data items obtained by edge detection of ring images and the data structure are different among the manufacturers of the systems. Generally, therefore, there is no data comparability among the manufacturers. It follows that corneal topography is analyzed based on point data for the data structure for each individual manufacturer. In addition, even for the same manufacturer, if the Placido ring structure is varied, it is necessary to change the analysis program and display program.